AiThority Interview with Vikram Murali, VP of Software Development, Application Modernization, and IT Automation at IBM

Vikram Murali, VP of Software Development, Application Modernization, and IT Automation at IBM, highlights more on the benefits of IBM Concert and how it empowers application teams, while taking us through the latest in GenAI and it’s impact on IT workflows:

_______

Hi Vikram, tell us about yourself and more about your role at IBM.

I’ve been part of the IBM family for almost two decades, wearing different hats and taking on leadership roles across various divisions. I have experience in working with various data warehousing appliances, database and information security products, data science and machine learning, next gen hybrid data stores, and Hadoop distributions. In my previous role, I lead development of watsonx.data lakehouse, part of the watsonx platform. In my current role as Vice President of Software Development, IBM Automation, I oversee the development of cutting-edge software solutions in the IT Automation and Network Automation Observability space, along with focus on driving app modernization and integration.

Also Read: Three Ways Generative AI Can Accelerate Knowledge Transfer Across An Organization

We’d love to know more about IBM Concert and how it enables end users?

Most application owners struggle with turning information from siloed data sources into actionable knowledge.  This challenge consumes an inordinate number of resources as application teams try to analyze, prioritize, and act based on the scattered data sources available to them.

IBM Concert provides a strategic view of applications across data sources, giving application teams the concrete recommendations they need to efficiently address the challenges their applications face. You can think of IBM Concert as the nerve center for your AI technology and operations.

IBM Concert uses AI to save application owners time and resources that usually go into analyzing and prioritizing hidden application data.  IBM Concert also produces more impactful outcomes by offering prioritized suggestions to guide the work of application teams.  Today, these outcomes focus on risk and compliance use cases, with additional use cases coming soon.

What are your predictions surrounding AI, GenAI and the future of business?

As we look forward, the initial allure and intrigue of early generative AI is transitioning into concrete business outcomes. This transformative technology is reshaping the way businesses boost productivity, encourage innovation, and spark creativity.

Open source pretrained AI models are expected to become increasingly popular, enabling businesses to boost growth by integrating these models with private or real-time data. This combination is set to improve productivity and cost-effectiveness.

We’ve also seen enterprises increasingly adopting customized generative AI applications that can meet their specific needs and provide more accurate responses based on proprietary data. This indicates a shift towards more tailored and efficient generative AI tools.

Also Read: AI For One and All

How can enhancements and innovations in GenAI specifically support IT teams in managing applications effectively across environments? What challenges do you still see IT teams struggle with as they implement AI powered tech to their daily functions?

GenAI can automate repetitive and mundane tasks, such as system monitoring, updates, and troubleshooting. IBM Concert specifically puts the user in the driver’s seat, providing application owners with a detailed understanding of their connected applications and toolsets. Concert can generate analyses, visualizations, and recommendations that enterprises can quickly turn into action. By helping organizations discover gaps, prioritize insights, and instrument changes, Concert helps reduce complexity and streamline operations to make their business more resilient, more innovative, and more cost-efficient.

The speed of application development and deployment is accelerating and will continue to do so in the coming years. This can overwhelm DevOps teams, particularly those who rely on manual efforts. To keep up with this rapid pace and advance their coding speeds, developers can use AI coding tools for generating code with greater efficiency and accuracy.

If you can also highlight how AI today enables IT teams to respect different compliance needs across regions, along with the biggest myths you feel IT teams still harbor when it comes to driving these kinds of processes with AI

AI-powered tools can help organizations fulfill compliance requirements by helping them effectively manage application performance and security certificates.

For example, IBM Concert’s automated visibility feature helps IT teams track certificate lifecycles, providing crucial insights into expiration dates and potential risks. This is particularly useful in managing compliance needs across different regions. IBM Concert also prioritizes certificates by their potential impact, allowing organizations to dedicate their time to renewals and minimize disruptions.

A common misconception among IT teams is that they don’t have the right skillset to drive these processes forward with AI. However, with the right educational resources, IT teams can quickly upskill themselves. Not only that, but the time saved from automating this process can also allow IT workers to focus on meaningful work or learning new skills.

Also Read: How the Art and Science of Data Resiliency Protects Businesses Against AI Threats

Five AI best practices you’d share with enterprise IT teams before we wrap up?

At IBM we believe that Artificial intelligence (AI) balanced with human oversight and accountability is crucial for AI lifecycle adoption. For this we recommend the following best practices:

1. Use AI to augment human intelligence, rather than operating independently of, or replacing it.
2. In a human-AI interaction, notify individuals that they are interacting with an AI system, and not a human being.
3. Design human-AI interactions to include and balance human oversight across the AI lifecycle. Address biases and promote human accountability and agency over outcomes by AI systems.
4. Develop policies and practices to foster inclusive and equitable access to AI technology, enabling a broad range of individuals to participate in the AI-driven economy.
5. Provide comprehensive employee training and reskilling programs to foster a diverse workforce that can adapt to the use of AI and share in the advantages of AI-driven innovations. Collaborate with HR to augment each employee’s scope of work.

For more on IBM recommendations and best practices; read here.

[To share your insights with us as part of editorial or sponsored content, please write to psen@itechseries.com]